Ghadimi, Pezhman and Donnelly, Oisin and Sar, Kubra and Wang, Chao and Azadnia, Amir Hossein
(2022)
The successful implementation of industry 4.0 in manufacturing: An analysis and prioritization of risks in Irish industry.
Technological Forecasting and Social Change, 175.
p. 121394.
ISSN 00401625
Abstract
Industry 4.0 is anticipated to revolutionize the manufacturing sector through a digital transformation. With this
transformation, many benefits are expected, such as the automation and decentralization of production pro-
cesses. Nevertheless, enterprises face considerable risks upon successful implementation of Industry 4.0. The
uncertainties regarding these risks are currently hindering enterprises’ implementation of Industry 4.0. Although
several studies have investigated the adoption of Industry 4.0-related technologies, far too little attention has
been devoted to identifying and analyzing the risk factors associated with the adoption of these technologies in
manufacturing, especially in Irish industry. Therefore, this study contributes to the existing knowledge by pro-
posing a systematic approach to identifying and ranking these risk factors along with recommending policies to
mitigate the highest risks. Fourteen risk factors are identified, and the opinions of 12 industry experts across the
Irish manufacturing sector are used to rank these risk factors using an adjusted best-worst method. The lack of
standards and lack of methodological approaches was the highest-ranking risk factor, with the risk to capital
investment, the lack of talent, the uncertainty in economic benefits and the potential delay to the manufacturing
process ranking in the top 5. Policy recommendations to mitigate the highest-ranking risks are proposed based on
an analysis of the Irish government’s current Industry 4.0 policy. Governments should aim to assist industries in
establishing comprehensive standards to increase the rate of successful Industry 4.0 implementation.
| Item Type: |
Article
|
| Keywords: |
Industry 4.0;
Risk factor;
Manufacturing;
Best-worst method;
Irish industry; |
| Academic Unit: |
Faculty of Social Sciences > School of Business |
| Item ID: |
17163 |
| Identification Number: |
https://doi.org/10.1016/j.techfore.2021.121394 |
| Depositing User: |
Amir Azadnia
|
| Date Deposited: |
09 May 2023 11:29 |
| Journal or Publication Title: |
Technological Forecasting and Social Change |
| Publisher: |
Elsevier |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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